code: def forward(self, x):
      bs = x.size(0)
      cur = self.stem(x)
  
      layers = [cur]
  
      for layer_id in range(self.num_layers):
          cur = self.layers[layer_id](layers)
          layers.append(cur)
          if layer_id in self.pool_layers_idx:
              for i, layer in enumerate(layers):
                  layers[i] = self.pool_layers[
                      self.pool_layers_idx.index(layer_id)
                  ](layer)
              cur = layers[-1]
  
      cur = self.gap(cur).view(bs, -1)
      cur = self.dropout(cur)
      logits = self.dense(cur)
      return logits
  
file_path: nni/examples/nas/legacy/oneshot/enas/macro.py
imports: import torch.nn
  from nni.nas.pytorch import mutables
  from ops import FactorizedReduce, ConvBranch, PoolBranch
label_desc: Use image node_id 2 for calling the GeneralNetwork obj's underlying member method code with example usage: obj.forward(x) and returns: logits